Google Cloud Storage and Azure Storage functions for working with unstructured data
Project description
Pyplatform is a data analytics platform architeture built around Google BigQuery in a hybrid cloud environment.
the platorm:
- provides fast, scalable and reliable SQL database solution
- abstracts away the infrastuture by builiding data pipelines with serverless compute solutions in python runtime environments
- simplifies development environment by using jupyter lab as the main tool
Installation
pip install pyplatform
Setting up development environment
git clone https://github.com/mhadi813/pyplatform
cd pyplatform
conda env create -f pyplatform_dev.yml
Environment variables
import os
os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = 'path/to/default_service_account.json'
os.environ['DATASET'] = 'default_bigquery_dataset_name'
os.environ['STORAGE_BUCKET'] = 'default_storage_bucket_id'
Usage
common data pipeline architectures:
- Http sources
- On-prem servers
- Bigquery integration with Azure Logic Apps
- Event driven ETL process
- Streaming pipelines
Exploring modules
import pyplatform as pyp
pyp.show_me()
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Close
Hashes for pyplatform-datalake-0.0.4.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2ff7f5c941a9773d2dc28d61b935afe5b302d2144e376502b81335454f7f00c4 |
|
MD5 | ccc2d3d27fd862155d48093768f4e410 |
|
BLAKE2b-256 | d26d7fd036faf0bbb1fbc47f9a8cf419effff256efbe52c1f94cf51df1303d62 |
Close
Hashes for pyplatform_datalake-0.0.4-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 5a58fc968b6c8b64a0cc713254d05a8b14c5bd2d084aef19c8f5368a3391ca2b |
|
MD5 | a31de9966aebacc95cb1491b2bb62261 |
|
BLAKE2b-256 | 5378d64ac52df1b68e016bf57077986f2598a416866bac7fc3f2a429bdff0277 |